Abstract
This article models, through Geostatistics, a database with space-time characteristics seeking to examine climate variations in the state of Bahia located in the Northeast region of Brazil. This dataset consists of information from 86 stations recorded by the National Institute of Meteorology (INMET) from January 2010 to December 2022 for the state. The focus of the analysis was to study the time series data related to air temperature. Initially, a descriptive analysis of the data was carried out and graphics were generated to understand the general climatic characteristics of the region, monthly. Then, Geostatistics was used to explore the structure of climate variations using semivariogram analysis to assess the spatial dependence of climate data, using ordinary kriging as an interpolating method for three theoretical models of semivariograms. The combination of the aforementioned methodologies allows the characterization of climate variations in the state of Bahia, in such a way that the discoveries can also contribute to the predictability of the climate in the region, providing insights for natural resource planning, agricultural management, climate prediction and adaptation strategies. The analysis was performed using the R programming language, which is recognized worldwide and used in climate studies.
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